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Introduction to Hands On Training in CORDEX South Asia Data Analysis

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Presentation on theme: "Introduction to Hands On Training in CORDEX South Asia Data Analysis"— Presentation transcript:

1 Introduction to Hands On Training in CORDEX South Asia Data Analysis
Module-1 J. Sanjay Centre for Climate Change Research (CCCR) Indian Institute of Tropical Meteorology (IITM), Pune (An Autonomous Institute of the Ministry of Earth Sciences, Govt. of India)

2 CORDEX-South Asia Evaluation Runs
available for Hands On Analyses & Visualization Institute Model Experiment Resolution Driving Model Driving Experiment IITM WRF3.1.1 BMJ Cu Scheme 50 km; Mercator ERA-Interim Global 0.75o RegCM3.0 Grell Cu Scheme Global 1.5o LMDZ AGCM Emanuel Cu Scheme 35 km; Variable Nudged with ERA-Interim Tiedtke Cu Scheme All RCM outputs regridded on a common region and 0.5o lat./lon. Grid in NetCDF Monthly/Daily mean Precipitation for the period

3 Network Common Data Form
NetCDF is a set of software libraries and self-describing machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data NetCDF Utilities ncdump reads a netCDF dataset and prints a textual representation of the information in the dataset ncdump –h file.nc prints the header information in a NetCDF file

4 Climate Data Operators
CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data (from MPIM Supported data formats are GRIB 1/2, netCDF 3/4, SERVICE, EXTRA and IEG. There are more than 600 operators available CDO has very small memory requirements and can process files larger than the physical memory CDO is open source Full documentation available as html or pdf from homepage ( CDO User’s Guide Version 1.6.1 CDO Reference Card

5 Grid Analysis and Display System
(from COLA GrADS is an interactive desktop tool that is used for easy access, manipulation, and visualization of earth science data GrADS has two data models for handling gridded and station data GrADS supports many data file formats, including binary (stream or sequential), GRIB (version 1 and 2), NetCDF, HDF (version 4 and 5), and BUFR (for station data) GrADS has been implemented worldwide on a variety of commonly used operating systems and is freely distributed over the Internet Online documentation has become the new standard for GrADS. Documentation page ( has User's Guide Tutorial useful Index for quick reference

6 Start Virtual Box Fedora14 Login User : CORDEX Passwd: cordex123
Structure of Files Start Virtual Box Fedora14 Login User : CORDEX Passwd: cordex123 Home Directory: /home/CORDEX/Desktop/Modules DATA Directories: OBS: Observation Data -Monthly RegCM/LMDZ/ARW: Model Data –Monthly ( ) OBS/DAILY: Daily Files ( ) What to do: CDO & GrADS Scripts $ cd scripts/CDA1 (Climate Data Analysis Module-1) $cd plot[1-5] (Change to each sub-module directory) Thanks to Sandip & Sabin

7 Climate Data Analysis Module: CDA1 (CORDEX South Asia: Climate model
Climate Data Analysis Module: CDA1 (CORDEX South Asia: Climate model outputs) – Mean & Variability Day 4: Friday, 30 August 2013 09:00 – 11:00 Hands on training: 1 (Trainers: J. Sanjay, Jayashree Revadekar, Rajiv Chaturvedi, Milind Mujumdar and Vimal Mishra) Precipitation Analyses and Visualization of: Observed Mean spatial patterns during Summer monsoon (JJAS) and Winter (DJF) seasons Comparison of RCMs simulated mean spatial patterns during Summer monsoon (JJAS) season Area averaged mean monthly annual cycle Comparison of RCMs simulated spatial patterns of interannual variability (standard deviation) during Summer monsoon (JJAS) season Temporal evolution of area averaged interannual variability (summer monsoon season anomalies normalized with standard deviation) Scripts provided: Analyses using CDO (Climate Data Operators) and visualization using GrADS (Graphical Analysis and Display System)

8 Precipitation Observed Mean Spatial patterns
during Summer monsoon (JJAS) and Winter (DJF) seasons File: CDA1/plot1/seasonal-mean.cdo Select months cdo -selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_ WA.nc CRU_precip_jjas.nc Time average over season cdo -timmean CRU_precip_jjas.nc CRU_precip_jjas_mean.nc File: CDA1/plot1/seasonal-mean.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot1/seasonal-mean.sh Unix shell script for CDO analysis & GrADS output Exercise: Please bring out the differences in the two seasons

9 Comparison of RCMs simulated mean precipitation spatial patterns
during Summer monsoon (JJAS) season File: CDA1/plot2/mul-mod-seasonal-mean.cdo Select JJAS months cdo -selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_ WA.nc CRU_precip_jjas.nc cdo -selmon,6,7,8,9 $DATADIR/LMDZ/LMDZ1_precip_mon_ WA.nc LMDZ1_precip_jjas.nc Compute JJAS mean & set relative time axis cdo -r -settaxis, ,00:00,1mon -timmean CRU_precip_jjas.nc CRU_precip_jjas-mean.nc cdo -r -settaxis, ,00:00,1mon -timmean LMDZ1_precip_jjas.nc LMDZ1_precip_jjas-mean.nc Compute Ensemble JJAS mean cdo -ensmean LMDZ1_precip_jjas-mean.nc LMDZ2…..nc RegCM…...nc ARW……..nc ENS_precip_jjas-mean.nc File: CDA1/plot2/mul-mod-seasonal-mean.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot2/mul-mod-seasonal-mean.sh Unix shell script for CDO analysis & GrADS output Exercise: Please bring out the differences in the simulations

10 Area averaged mean monthly annual cycle of precipitation
File: CDA1/plot3/annual-cycle.cdo Compute monthly mean climatology cdo -ymonmean $DATADIR/OBS/CRU_precip_mon_ WA.nc CRU_precip_mon_CLIM.nc cdo -ymonmean $DATADIR/LMDZ/LMDZ1_precip_mon_ WA.nc LMDZ1_precip_mon_CLIM.nc Select region cdo -sellonlatbox,70,90,10,25 CRU_precip_mon_CLIM.nc CRU_precip_mon_CLIM_IND.nc cdo -sellonlatbox,70,90,10,25 LMDZ1_precip_mon_CLIM.nc LMDZ1_precip_mon_CLIM_IND.nc Area average cdo -fldmean CRU_precip_mon_CLIM_IND.nc CRU_precip_mon_CLIM_IND_fldmean.nc cdo -fldmean LMDZ1_precip_mon_CLIM_IND.nc LMDZ1_precip_mon_CLIM_IND_fldmean.nc Set relative time axis cdo -r -settaxis, ,12:00,1mon CRU_precip_mon_CLIM_IND_fldmean.nc CRU_precip_mon_CLIM_IND_fldmean-n.nc cdo -r -settaxis, ,12:00,1mon LMDZ1_precip_mon_CLIM_IND_fldmean.nc LMDZ1_precip_mon_CLIM_IND_fldmean-n.nc File: CDA1/plot3/annual-cycle.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot3/annual-cycle.sh Unix shell script for CDO analysis & GrADS output Exercise: Please bring out the differences in the annual cycle Analyse for a region of your choice

11 precipitation interannual variability (standard deviation)
Comparison of RCMs simulated spatial patterns of summer monsoon (JJAS) season precipitation interannual variability (standard deviation) File: CDA1/plot4/mul-mod-seasonal-std.cdo Select JJAS months & seasonal mean for each year cdo -yearmean -selmon,6/9 $DATADIR/OBS/CRU_precip_mon_ WA.nc CRU_precip_jjas.nc cdo -yearmean -selmon,6/9 $DATADIR/LMDZ/LMDZ1_precip_mon_ WA.nc LMDZ1_precip_jjas.nc Compute standard deviation of JJAS mean cdo -timstd CRU_precip_jjas.nc CRU_precip_jjas-timstd.nc cdo -timstd LMDZ1_precip_jjas.nc LMDZ1_precip_jjas-timstd.nc File: CDA1/plot4/mul-mod-seasonal-std.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot4/mul-mod-seasonal-std.sh Unix shell script for CDO analysis & GrADS output Exercise: Please bring out the differences in the simulations

12 Temporal evolution of area averaged of summer monsoon (JJAS) season precipitation
interannual variability (seasonal anomalies normalized with standard deviation) File: CDA1/plot5/IAV.cdo Compute JJAS mean for each year cdo -selmon,6,7,8,9 $DATADIR/CRU_precip_mon_ WA.nc CRU_precip_jjas.nc cdo -yearmean CRU_precip_jjas.nc CRU_precip_jjas-mean.nc Select region and area average cdo -sellonlatbox,70,90,10,25 CRU_precip_jjas-mean.nc CRU_precip_jjas-mean-IND.nc cdo -fldmean CRU_precip_jjas-mean-IND.nc CRU_precip_jjas-mean-IND-fldmean.nc Compute area averaged seasonal anomalies cdo -timmean CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-timmean.nc cdo -sub CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-timmean.nc CRU_precip_jjas-mean-IND-anom.nc Prepare the observed summer monsoon precipitation index cdo -timstd CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-std.nc cdo -div CRU_precip_jjas-mean-IND-anom.nc CRU_precip_jjas-mean-IND-fldmean-std.nc CRU_precip_jjas-mean-IND-std-fldmean.nc cdo -r -settaxis, ,00:00,1year CRU_precip_jjas-mean-IND-std-fldmean.nc CRU_precip_jjas-mean-IND-std-fldmean-n.nc File: CDA1/plot5/IAV.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot5/IAV.sh Unix shell script for CDO analysis & GrADS output Exercise: Please indicate the extreme monsoon years

13 Comparison of RCMs simulated Summer monsoon (JJAS) season mean precipitation bias
File: CDA1/plot6/mul-mod-seas-mean-bias.cdo Compute JJAS long-term mean bias cdo -sub ../plot2/LMDZ1_precip_jjas-mean.nc ../plot2/CRU_precip_jjas-mean.nc LMDZ1_precip_jjas-bias.nc File: CDA1/plot6/mul-mod-seas-mean-bias.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot6/mul-mod-seas-mean-bias.sh Unix shell script for CDO analysis & GrADS output

14 Comparison of RCMs simulated and Observed Summer monsoon (JJAS) season mean precipitation Coefficient of Variation (CV = Standard Deviation / Mean) File: CDA1/plot7/mul-mod-seas-mean-cv.cdo Compute JJAS mean CV cdo -mulc, div ../plot4/CRU_precip_jjas-timstd.nc ../plot2/CRU_precip_jjas-mean.nc CRU_precip_jjas-cv.nc cdo -mulc, div ../plot4/LMDZ1_precip_jjas-timstd.nc ../plot2/LMDZ1_precip_jjas-mean.nc LMDZ1_precip_jjas-cv.nc File: CDA1/plot7/mul-mod-seas-mean-cv.gs GrADS script to plot & prepare output in EPS format File: CDA1/plot7/mul-mod-seas-mean-cv.sh Unix shell script for CDO analysis & GrADS output

15 Thanks for your attention
Many Thanks to: My Team members Sabin & Sandip Thanks for your attention

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